AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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A multi-agent harness that represents each request as a persistent, artifact-grounded analysis run, and demonstrates that reliable bioinformatics automation depends not only on model capability, but also on the harness that governs planning, execution, memory, and evidence flow.
This work exposes lazy grounding by injecting nearby evidence from answer-changing rewrites of benchmark questions into the search corpora, and shows that robust search agents must defend against not only misinformation but also the misapplication of factual evidence.
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